Abstract
P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as "true" P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function.
| Original language | English |
|---|---|
| Pages (from-to) | 6924-6943 |
| Number of pages | 20 |
| Journal | International Journal of Molecular Sciences |
| Volume | 13 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2012 |
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Keywords
- Classification model
- Consensus model
- Decision trees
- MDR1 ligands
- P-glicoprotein
- P-gp inhibitors
ASJC Scopus subject areas
- Computer Science Applications
- Molecular Biology
- Catalysis
- Inorganic Chemistry
- Spectroscopy
- Organic Chemistry
- Physical and Theoretical Chemistry
- Medicine(all)
Cite this
Development of classification models for identifying "true" P-glycoprotein (P-gp) inhibitors through inhibition, ATPase activation and monolayer efflux assays. / Rapposelli, Simona; Coi, Alessio; Imbriani, Marcello; Bianucci, Anna Maria.
In: International Journal of Molecular Sciences, Vol. 13, No. 6, 06.2012, p. 6924-6943.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Development of classification models for identifying "true" P-glycoprotein (P-gp) inhibitors through inhibition, ATPase activation and monolayer efflux assays
AU - Rapposelli, Simona
AU - Coi, Alessio
AU - Imbriani, Marcello
AU - Bianucci, Anna Maria
PY - 2012/6
Y1 - 2012/6
N2 - P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as "true" P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function.
AB - P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as "true" P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function.
KW - Classification model
KW - Consensus model
KW - Decision trees
KW - MDR1 ligands
KW - P-glicoprotein
KW - P-gp inhibitors
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UR - http://www.scopus.com/inward/citedby.url?scp=84862502518&partnerID=8YFLogxK
U2 - 10.3390/ijms13066924
DO - 10.3390/ijms13066924
M3 - Article
VL - 13
SP - 6924
EP - 6943
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
SN - 1661-6596
IS - 6
ER -